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Research was conducted on parents’ experience of caring for a child living with Duchenne muscular dystrophy (DMD). The focus of this research was on the key psychological aspects of the process of adjustment to the illness of their child (family and spousal relationship, daily life, emotions, career, spirituality, and coping strategies). There was evidence throughout the study of gender‐specific differences in constructing the different aspects of the shared experience. The main findings included major differences in the initial reaction and coping styles between mothers and fathers. These differences could be perceived as a threat or could serve as a source of isolation between parents. Additional findings included the unequal sharing of caregiving tasks between partners: the primary caregiving role usually being assumed by the mother, with the father playing a supportive role. The unique contribution of this study in further describing the lived experience of parents of a child with DMD is its attention to the internal dynamic of the relationship between mothers and fathers. This dynamic is highly dependent on the respective roles of primary and secondary caregiver. This research has implications for the design and implementation of intervention strategies aimed at couples caring for a child with DMD, or with other severe, chronic, and uniformly fatal illnesses.

Impairment of intelligence in Duchenne muscular dystrophy (DMD) patients was described by Duchenne de Boulogne himself in 1868. Further studies report intelligence disorders with mayor impairment of memory. The aim of the present study was to assess the presence of affective and personality disorders in a group of children affected by DMD. Twenty six male DMD patients, mean age eleven and four months years old, were assessed for their affective and personality disorder. Only eight subjects had a total IQ below average with major difficulties in verbal and visual-spatial memory, comprehension, arithmetic and vocabulary. All the subjects presented some disorders: tendency to marginalization and isolation, self-depreciation, sense of insecurity, hypochondriac thoughts and marked state of anxiety. These disorders are often a dynamic prolongation of a psychological process which starts when the diagnosis is made and continues, in a slow and latent fashion, throughout the evolution of the disease.

Diagnosing genetic neuromuscular disorder such as muscular dystrophy is complicated when the imperfection occurs while splicing. This paper aims in predicting the type of muscular dystrophy from the gene sequences by extracting the well-defined descriptors related to splicing mutations. An automatic model is built to classify the disease through pattern recognition techniques coded in python using scikit-learn framework.

In this paper, the cloned gene sequences are synthesized based on the mutation position and its location on the chromosome by using the positional cloning approach. For instance, in the human gene mutational database (HGMD), the mutational information for splicing mutation is specified as IVS1-5 T > G indicates (IVS - intervening sequence or introns), first intron and five nucleotides before the consensus intron site AG, where the variant occurs in nucleotide G altered to T. IVS (+ve) denotes forward strand 3′– positive numbers from G of donor site invariant and IVS (−ve) denotes backward strand 5′ – negative numbers starting from G of acceptor site. The key idea in this paper is to spot out discriminative descriptors from diseased gene sequences based on splicing variants and to provide an effective machine learning solution for predicting the type of muscular dystrophy disease with the splicing mutations. Multi-class classification is worked out through data modeling of gene sequences. The synthetic mutational gene sequences are created, as the diseased gene sequences are not readily obtainable for this intricate disease. Positional cloning approach supports in generating disease gene sequences based on mutational information acquired from HGMD. SNP-, gene- and exon-based discriminative features are identified and used to train the model. An eminent muscular dystrophy disease prediction model is built using supervised learning techniques in scikit-learn environment. The data frame is built with the extracted features as numpy array. The data are normalized by transforming the feature values into the range between 0 and 1 aid in scaling the input attributes for a model. Naïve Bayes, decision tree, K-nearest neighbor and SVM learned models are developed using python library framework in scikit-learn.

To the best knowledge of authors, this is the foremost pattern recognition model, to classify muscular dystrophy disease pertaining to splicing mutations. Certain essential SNP-, gene- and exon-based descriptors related to splicing mutations are proposed and extracted from the cloned gene sequences. An eminent model is built using statistical learning technique through scikit-learn in the anaconda framework. This paper also deliberates the results of statistical learning carried out with the same set of gene sequences with synonymous and non-synonymous mutational descriptors.

The data frame is built with the Numpy array. Normalizing the data by transforming the feature values into the range between 0 and 1 aid in scaling the input attributes for a model. Naïve Bayes, decision tree, K-nearest neighbor and SVM learned models are developed using python library framework in scikit-learn. While learning the SVM model, the cost, gamma and kernel parameters are tuned to attain good results. Scoring parameters of the classifiers are evaluated using tenfold cross-validation using metric functions of scikit-learn library. Results of the disease identification model based on non-synonymous, synonymous and splicing mutations were analyzed.

Certain essential SNP-, gene- and exon-based descriptors related to splicing mutations are proposed and extracted from the cloned gene sequences. An eminent model is built using statistical learning technique through scikit-learn in the anaconda framework. The performance of the classifiers are increased by using different estimators from the scikit-learn library. Several types of mutations such as missense, non-sense and silent mutations are also considered to build models through statistical learning technique and their results are analyzed.

To the best knowledge of authors, this is the foremost pattern recognition model, to classify muscular dystrophy disease pertaining to splicing mutations.

Students with physical and health impairments represent a small but growing group of individuals with diverse educational needs. They are those students whose physical limitations or health problems interfere with school attendance or learning to such an extent that special services, training, equipment, materials, or facilities are required. Therefore, the purpose of this chapter is to discuss some of these impairments and acquaint both general and special educators with interventions for helping students with physical and health impairments succeed.

The purpose of this paper is to build an understanding of what we term “consumer discipline” by unpacking the practices and strategies by which people manage and exert control over what they consume. This is facilitated by looking at the context of food, an everyday necessity imbued with sizeable importance in terms of its impact on personal well-being, and how it is experienced by individuals who must manage the constraints of a chronic illness.

Drawing on the Foucauldian concept of governmentality and theories surrounding the social facilitation of self-management, this paper analyses interviews with 17 consumers diagnosed with diabetes or coronary heart disease.

By exploring how the chronically ill generate different strategies in managing what they eat and how they think about it, this paper outlines four analytical areas to continue the discussion of how consumption is disciplined and its conceptualisation in marketing and health-related research: “the Individual”, “the Other”, “the Market” and “the Object”.

The results signal to policymakers the aspects of health promotion that can be enhanced to improve self-management amongst consumers in the pursuit of well-being.

This paper makes two contributions: it conceptualises consumer discipline as a practice that involves self-control but also comprises the capabilities to self-manage one’s identity and relationships through leveraging personal and social strategies across various contexts; and it identifies macro influences such as the market as negotiable powers that can be contested or resisted to help assist in one’s self-management.

The progress of genetic medicine has given rise to recent changes in the field of health care, such as expected benefits and potential risks for patients and their relatives. Individual genetic information can unlock many secrets within the genetic family and, sometimes the community to which he or she belongs. Therefore, the traditional duty of confidentiality owed by a health care professional to a patient has been challenged by the more serious discussions based on new genetics. Clinical geneticists providing genetic services must be aware of such complicated situations and whenever possible offer support to the patient (client) and their family members. Excluding eugenics and nonscientific perspectives, the Japanese government renamed and reworked “The Eugenic Protection Act” into the “Maternal Heath Protection Act” in 1996. From 1995 to 2003, the Japanese Society of Human Genetics (JSHG) revised guidelines for genetic testing three times. This process attempted to clarify indications for genetic testing, to focus on protection of individual genetic privacy and to deepen respect for familial relationships and responsibilities. The survey involving 221 JSHG approved clinical geneticist (response rate 54%) revealed that during last 5 years the number trying to do “non-directive” rather than “directive” counseling increased significantly. Although there is still in confusion on certain issues, such as data disclosure to relatives, the global bioethical view of new genetics is gaining Japanese geneticists’ acceptance.